GEOINT = “Analytics Superfood”

“Geospatial data is analytics superfood,” according to Jeff Jonas, IBM fellow and chief scientist of context computing. Jonas gave the opening keynote address April 25 at USGIF’s Data Analytics Workshop in Herndon, Va. More than 200 people attended the workshop, sponsored by NVIDIA and DigitalGlobe, to hear from data science experts in government, industry, and academia.

Jonas’ speech, titled “Context Computing and Geospatial Superfood,” began by introducing the concept of “context computing”—gaining a better understanding of something by taking into account the things around it—and “context accumulation,” the incremental process of layering new observations on top of those made previously. Putting data into context generates better predictions, and as the database grows more data means less compute time, he added, noting how the last few pieces of a jigsaw puzzle are often the easiest.

Jonas has applied context computing to create what he calls the “space time box,” which determines how objects co-locate each other when they’re traveling. The country of Singapore uses a 2D version of Jonas’ space time box for vessel tracking and maritime domain awareness. More recently, he added a third dimension to help the University of Honolulu’s Institute of Astronomy track asteroids. Space time box now forecasts how more than 600,000 asteroids will interact over the next 25 years. When a new asteroid is discovered, space time box takes only 15 minutes to discern how it will interact with all other asteroids and whether it’s a potential danger to Earth.

Jonas concluded by encouraging the audience to read his “Fantasy Analytics” blog post and “widen their observation spaces.”

“It’s about what other data you would be able to get your hands on … should you bring that to bear it will help create closure on your puzzle so you can get really high-quality predictions,” he said.

The workshop also included panels on deep learning, analytic challenges, and anticipatory analytics, as well as industry lightning talks.

Presenting Challenges

In the analytic challenges panel, Intelligence Community leaders shared their challenges with industry. Terry Busch, chief of the Defense Intelligence Agency’s (DIA) integrated analysis and methodologies division, said rather than huddle up in a “team of trust,” the agency is becoming more externally focused than ever before and challenging industry to help it answer its most deep-diving questions and also to facilitate culture change.

Busch said he seeks solutions to help the DIA analytic community transition from qualitative to deep quantitative analysis.

“I’m looking for answers in UX design to make this cultural change a little more tolerable,” he said. “We need to transition technology and we need those technologies to be palatable and understandable.”

Todd Johanesen, director of the office of sciences and methodologies with the National Geospatial-Intelligence Agency (NGA), asked industry to help the agency advance object-based production and structured observation management—capturing and sharing all the GEOINT possible about an object—in support of activity-based intelligence.

“As today’s data sets are increasing and the timeliness of us reporting out that information decreases, people want the information as soon as or even before we’re able to look at it,” Johanesen said. “We have to come up with other means to collect that, understand it, and push what we know about those data sets out.”

“If you don’t have some sort of ground truth to measure your forecast against, you have no way to know whether your algorithm is any good and no way to convince an analyst they should pay attention to it,” McCormick said.

Toward the Future

During the panel on deep learning, Tom Reed, director of solution architecture for GPU-provider NVIDIA, said despite how much deep learning is “hyped” right now he believes experts might actually be under-predicting how fast it is going to evolve.

“Deep learning is already touching all of our lives,” he said … “We have to accept the fact that this technology is going to be part of our lives, and having some notion of the technology is incumbent upon us or we run the risk of not being able to manage the exploitation of it. It’s going to be everywhere.”

Juliane Gallina, director of Watson Government Solutions with IBM, said government investment in Amazon C2S and other types of cloud computing is facilitating the applications of machine learning in the Intelligence Community and also in other areas such as medicine.

Dr. Lisa Porter, executive vice president and director of CosmiQ Works, In-Q-Tel, gave a closing keynote on commercial space. Porter posited we are in “Space 3.0,” which is driven by venture-based startups producing a new wave of affordable products and services.

“[Space] 3.0 is driven by cost and innovation, and the essence of 3.0 is all about affordability and scalability,” Porter said. “Multiple submarkets have to work together to make this vision a reality.”

Porter announced that CosmiQ Works and DigitalGlobe, with assistance from NVIDIA and USGIF, have partnered to create a Satellite Imagery Object Detection Challenge, a competition to evaluate algorithms to advance object detection in satellite imagery. The challenge will be the first in an ongoing series of challenges, and teams will use SpaceNet, a corpus of high-resolution satellite imagery and labeled training data, to develop and train algorithms.

“Let’s run this challenge, provide the data, let people put their algorithms to the test, and see what we get,” Porter said. “I’m very excited about this because it represents an opportunity for the community to leverage all the good work going on and tailor it to our specific challenges and needs.”

The specific task for the 2016 challenge will be announced in the coming weeks and a development kit will also be released.

Visit the USGIF website to learn more about future workshops and other events.